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<p>This study develops a risk network model using social network analysis (SNA) to address the complex interdependencies among risk factors in municipal engineering projects contracted by Chinese firms in Saudi Arabia. The four-type risk classification framework (Types I-IV) was introduced to categorize risks based on their network positions and characteristics. A case study of a large-scale municipal project was conducted, and the results showed that 34 risk factors were classified into 4 Type I risks, 2 Type II risks, 17 Type III risks, and 11 Type IV risks. Based on the network analysis, tailored preemptive and post-emergency response strategies were formulated for each risk type. Furthermore, a system dynamics simulation was employed for scene analysis of the proposed strategies. The simulation results demonstrated a significant improvement, with the project completion rate increasing from 77 to 90.5% after implementing the targeted risk responses. This work provides a systematic approach for Chinese contractors to understand risk propagation mechanisms and select optimal control strategies, thereby enhancing project success in the Saudi Arabian market.</p>

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Risk network analysis and simulation research in municipal engineering projects contracted by China in Saudi Arabia

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月7日

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  • Rami Talal T Alotaibi

摘要

This study develops a risk network model using social network analysis (SNA) to address the complex interdependencies among risk factors in municipal engineering projects contracted by Chinese firms in Saudi Arabia. The four-type risk classification framework (Types I-IV) was introduced to categorize risks based on their network positions and characteristics. A case study of a large-scale municipal project was conducted, and the results showed that 34 risk factors were classified into 4 Type I risks, 2 Type II risks, 17 Type III risks, and 11 Type IV risks. Based on the network analysis, tailored preemptive and post-emergency response strategies were formulated for each risk type. Furthermore, a system dynamics simulation was employed for scene analysis of the proposed strategies. The simulation results demonstrated a significant improvement, with the project completion rate increasing from 77 to 90.5% after implementing the targeted risk responses. This work provides a systematic approach for Chinese contractors to understand risk propagation mechanisms and select optimal control strategies, thereby enhancing project success in the Saudi Arabian market.